L-tyrosine Positron Emission Tomography Research Articles

Dummy run for planning of isotoxic dose-escalated radiation therapy for glioblastoma used in the PRIDE trial (NOA-28; ARO-2024-01; AG-NRO-06)

BackgroundThe PRIDE trial (NOA-28; ARO-2024-01; AG-NRO-06; NCT05871021) is designed to determine whether a dose escalation with 75.0 Gy in 30 fractions can enhance the median overall survival (OS) in patients with methylguanine methyltransferase (MGMT) promotor unmethylated glioblastoma compared to historical median OS rates, while being isotoxic to historical cohorts through the addition of concurrent bevacizumab (BEV). To ensure protocol-compliant irradiation planning with all study centers, a dummy run was planned and the plan quality was evaluated. MethodsA suitable patient case was selected and the computed tomography (CT), magnetic resonance imaging (MRI) and O-(2-[18F]fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) contours were made available. Participants at the various intended study sites performed radiation planning according to the PRIDE clinical trial protocol. The treatment plans and dose grids were uploaded as Digital Imaging and Communications in Medicine (DICOM) files to a cloud-based platform. Plan quality and protocol adherence were analyzed using a standardized checklist, scorecards and indices such as Dice Score (DSC) and Hausdorff Distance (HD). ResultsMedian DSC was 0.89, 0.90, 0.88 for PTV60, PTV60ex (planning target volume receiving 60.0 Gy for the standard and the experimental plan, respectively) and PTV75 (PTV receiving 75.0 Gy in the experimental plan), respectively. Median HD values were 17.0 mm, 13.9 mm and 12.1 mm, respectively. These differences were also evident in the volumes: The PTV60 had a volume range of 219.1–391.3 cc (median: 261.9 cc) for the standard plans, while the PTV75 volumes for the experimental plans ranged from 71.5–142.7 cc (median: 92.3 cc). The structures with the largest deviations in Dice score were the pituitary gland (median 0.37, range 0.00–0.69) and the right lacrimal gland (median 0.59, range 0.42–0.78). ConclusionsThe deviations revealed the necessity of systematic trainings with appropriate feedback before the start of clinical trials in radiation oncology and the constant monitoring of protocol compliance throw-out the study. Trial registrationNCT05871021

The Traumatic Inoculation Process Affects TSPO Radioligand Uptake in Experimental Orthotopic Glioblastoma.

The translocator protein (TSPO) has been proven to have great potential as a target for the positron emission tomography (PET) imaging of glioblastoma. However, there is an ongoing debate about the potential various sources of the TSPO PET signal. This work investigates the impact of the inoculation-driven immune response on the PET signal in experimental orthotopic glioblastoma. Serial [18F]GE-180 and O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) PET scans were performed at day 7/8 and day 14/15 after the inoculation of GL261 mouse glioblastoma cells (n = 24) or saline (sham, n = 6) into the right striatum of immunocompetent C57BL/6 mice. An additional n = 25 sham mice underwent [18F]GE-180 PET and/or autoradiography (ARG) at days 7, 14, 21, 28, 35, 50 and 90 in order to monitor potential reactive processes that were solely related to the inoculation procedure. In vivo imaging results were directly compared to tissue-based analyses including ARG and immunohistochemistry. We found that the inoculation process represents an immunogenic event, which significantly contributes to TSPO radioligand uptake. [18F]GE-180 uptake in GL261-bearing mice surpassed [18F]FET uptake both in the extent and the intensity, e.g., mean target-to-background ratio (TBRmean) in PET at day 7/8: 1.22 for [18F]GE-180 vs. 1.04 for [18F]FET, p < 0.001. Sham mice showed increased [18F]GE-180 uptake at the inoculation channel, which, however, continuously decreased over time (e.g., TBRmean in PET: 1.20 at day 7 vs. 1.09 at day 35, p = 0.04). At the inoculation channel, the percentage of TSPO/IBA1 co-staining decreased, whereas TSPO/GFAP (glial fibrillary acidic protein) co-staining increased over time (p < 0.001). We identify the inoculation-driven immune response to be a relevant contributor to the PET signal and add a new aspect to consider for planning PET imaging studies in orthotopic glioblastoma models.

Multiparametric Analysis Combining DSC-MR Perfusion and [18F]FET-PET is Superior to aSingle Parameter Approach for Differentiation of Progressive Glioma from Radiation Necrosis.

Perfusion-weighted (PWI) magnetic resonance imaging (MRI) and O‑(2-[18F]fluoroethyl-)-l-tyrosine ([18F]FET) positron emission tomography (PET) are both useful for discrimination of progressive disease (PD) from radiation necrosis (RN) in patients with gliomas. Previous literature showed that the combined use of FET-PET and MRI-PWI is advantageous; hhowever the increased diagnostic performances were only modest compared to the use of asingle modality. Hence, the goal of this study was to further explore the benefit of combining MRI-PWI and [18F]FET-PET for differentiation of PD from RN. Secondarily, we evaluated the usefulness of cerebral blood flow (CBF), mean transit time (MTT) and time to peak (TTP) as previous studies mainly examined cerebral blood volume (CBV). In this single center study, we retrospectively identified patients with WHO gradesII-IV gliomas with suspected tumor recurrence, presenting with ambiguous findings on structural MRI. For differentiation of PD from RN we used both MRI-PWI and [18F]FET-PET. Dynamic susceptibility contrast MRI-PWI provided normalized parameters derived from perfusion maps (r(relative)CBV, rCBF, rMTT, rTTP). Static [18F]FET-PET parameters including mean and maximum tumor to brain ratios (TBRmean, TBRmax) were calculated. Based on histopathology and radioclinical follow-up we diagnosed PD in 27and RN in 10cases. Using the receiver operating characteristic (ROC) analysis, area under the curve (AUC) values were calculated for single and multiparametric models. The performances of single and multiparametric approaches were assessed with analysis of variance and cross-validation. After application of inclusion and exclusion criteria, we included 37patients in this study. Regarding the in-sample based approach, in single parameter analysis rTBRmean (AUC = 0.91, p < 0.001), rTBRmax (AUC = 0.89, p < 0.001), rTTP (AUC = 0.87, p < 0.001) and rCBVmean (AUC = 0.84, p < 0.001) were efficacious for discrimination of PD from RN. The rCBFmean and rMTT did not reach statistical significance. Aclassification model consisting of TBRmean, rCBVmean and rTTP achieved an AUC of 0.98 (p < 0.001), outperforming the use of rTBRmean alone, which was the single parametric approach with the highest AUC. Analysis of variance confirmed the superiority of the multiparametric approach over the single parameter one (p = 0.002). While cross-validation attributed the highest AUC value to the model consisting of TBRmean and rCBVmean, it also suggested that the addition of rTTP resulted in the highest accuracy. Overall, multiparametric models performed better than single parameter ones. Amultiparametric MRI-PWI and [18F]FET-PET model consisting of TBRmean, rCBVmean and PWI rTTP significantly outperformed the use of rTBRmean alone, which was the best single parameter approach. Secondarily, we firstly report the potential usefulness of PWI rTTP for discrimination of PD from RN in patients with glioma; however, for validation of our findings the prospective studies with larger patient samples are necessary.

Comparison between [68Ga]Ga-PSMA-617 and [18F]FET PET as Imaging Biomarkers in Adult Recurrent Glioblastoma.

The aim of this prospective clinical study was to evaluate the potential of the prostate specific membrane antigen (PSMA) targeting ligand, [68Ga]-PSMA-Glu-NH-CO-NH-Lys-2-naphthyl-L-Ala-cyclohexane-DOTA ([68Ga]Ga-PSMA-617) as a positron emission tomography (PET) imaging biomarker in recurrent glioblastoma patients. Patients underwent [68Ga]Ga-PSMA-617 and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET scans on two separate days. [68Ga]Ga-PSMA-617 tumour selectivity was assessed by comparing tumour volume delineation and by assessing the intra-patient correlation between tumour uptake on [68Ga]Ga-PSMA-617 and [18F]FET PET images. [68Ga]Ga-PSMA-617 tumour specificity was evaluated by comparing its tumour-to-brain ratio (TBR) with [18F]FET TBR and its tumour volume with the magnetic resonance imaging (MRI) contrast-enhancing (CE) tumour volume. Ten patients were recruited in this study. [68Ga]Ga-PSMA-617-avid tumour volume was larger than the [18F]FET tumour volume (p = 0.063). There was a positive intra-patient correlation (median Pearson r = 0.51; p < 0.0001) between [68Ga]Ga-PSMA-617 and [18F]FET in the tumour volume. [68Ga]Ga-PSMA-617 had significantly higher TBR (p = 0.002) than [18F]FET. The [68Ga]Ga-PSMA-617-avid tumour volume was larger than the CE tumour volume (p = 0.0039). Overall, accumulation of [68Ga]-Ga-PSMA-617 beyond [18F]FET-avid tumour regions suggests the presence of neoangiogenesis in tumour regions that are not overly metabolically active yet. Higher tumour specificity suggests that [68Ga]-Ga-PSMA-617 could be a better imaging biomarker for recurrent tumour delineation and secondary treatment planning than [18F]FET and CE MRI.

NIMG-23. COMBINATION OF ADC MRI AND FET PET FOR THE ASSESSMENT OF QUANTITATIVE TUMOR PRESENCE IN DIFFUSE GLIOMA

Abstract BACKGROUND Local treatment of diffuse glioma is currently guided by standard MRI sequences. Yet, the combination of apparent diffusion coefficient (ADC) and O-(2-[18F]-fluoroethyl)-L-tyrosine positron emission tomography (FET PET) (ADC/FET) detects qualitatively assessed histopathological tumor presence more accurately than standard MRI imaging. It is unknown whether this is similar for quantitatively assessment of tumor presence. This study compares the diagnostic accuracy of standard imaging and ADC/FET for detecting quantitatively assessment of tumor presence in diffuse glioma. METHODS Fifteen patients with newly diagnosed diffuse glioma were retrospectively included. Pre-operative MRI and FET PET imaging were available. Multiregional image-guided stereotactic biopsies were acquired before craniotomy. Quantitative imaging data from regions-of-interests (ROIs) centered at the biopsy locations was obtained. For each biopsy sample, semi-automatic cellularity and proliferation index, as well as DNA methylation-based tumor purity, was determined. Linear mixed models were used to evaluate which modalities were significant independent predictors for each tumor presence marker, and fitness was assessed using Bayesian Information Criterium. RESULTS 125 biopsies were analyzed (75 from eight high grade and 50 from seven low grade gliomas). Cellularity was associated with T1 weighted MRI (p = 0.033), ADC (p = 0.016) and ADC/FET (p &amp;lt; .001), with ADC/FET as best fit. ADC/FET was the only modality associated with proliferation index (p = 0.003) and with tumor purity (p &amp;lt; .001). CONCLUSION Combined ADC and FET PET is stronger associated with cellularity, proliferation index and tumor purity than standard MRI imaging. These findings may pave the way towards ADC/FET-guided local treatment of diffuse gliomas.

P05.02.A PRELIMINARY FINDINGS FROM THE MRI QUALITY ASSURANCE PROGRAMME FOR THE PROSPECTIVE MULTI-SITE AUSTRALIAN FIG ([FET-PET IN GLIOBLASTOMA) TROG 18.06 STUDY

Abstract BACKGROUND The O-(2-[18F]-fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) in Glioblastoma (FIG) study is a prospective study evaluating the management impact of FET-PET imaging in up to 210 newly diagnosed adult glioblastoma patients across 10 Australian sites. Patients undergo contrast MRI and FET-PET at 3 timepoints: pre-chemoradiotherapy (CRT), one-month post-CRT and at suspected progression. MRI QA programme components, approach and integrated workflows are described here. MATERIAL AND METHODS The FIG MRI protocol comprised 3D-T1, 3D-FLAIR, Axial 2D DWI (including derived ADC map), DCE (including T1 mapping), DSC, Axial T2 and 3D T1-post-contrast (T1C) sequences, with SWI and 3D DIR sequences optional. QA components included data acquisition quality and completeness (standard and advanced), motion artefact, low contrast to noise or signal to noise, series description and susceptibility artifacts. Suitability of T1/T1C using modified RANO (mRANO) criteria was assessed. An optimised workflow involved site upload from local PACS systems to centralised database via TROG Central Quality Management System (CQMS) platform and collation into a central imaging database utilising MIM software. The MRI QA workflow encompassed automated anonymisation of DICOM data, data completeness and reconstruction evaluation, then review by two expert neuroimaging analysts. Sites received feedback with request for resubmission where required. RESULTS Between December 2021 and February 2023, MRI data in 74 patients across 9 sites with median of 6 patients (range 2-17) per site was submitted. A total of 141 MRI datasets across all timepoints were collected (per site range:4-35, median:13), with 43 imaging time-points selected for QA (per site range:3-12, median: 4). Importantly, 41/43 (95%) of initial datasets were deemed suitable for mRANO assessment, but only 13/43 (30%) were suitable for advanced MRI analysis. Very few datasets had motion or susceptibility artifacts, low contrast to noise or signal to noise, or incorrect series description. Technical issues identified included incomplete data (DCE - missing T1 maps, DWI - missing ADC maps), incorrect sequence reconstruction (DCE split series and Axial/Sagittal/Coronal reformats for 3D images) and lack of non-mandatory SWI sequences. Feedback to sites resulted in improvements in DCE sequence acquisition from split series in 11/45 (24%) to preferred single series in 18/24 (75%) and similar increases in T1 maps completeness from 7/19 (37%) to 7/7 (100%). CONCLUSION Despite challenges in multisite workflow and substantial multi-modality site and central data management, a robust MRI QA program has confirmed 95% compliance for mRANO assessment. Site specific feedback resulted in increased compliance with advanced MRI sequences to enable detailed future analysis.

JS09.7.A COMBINATION OF APPARENT DIFFUSION COEFFICIENT AND FET PET COMPARED WITH STANDARD IMAGING FOR QUANTITATIVE TUMOR PRESENCE IN DIFFUSE GLIOMAS

Abstract BACKGROUND Diffuse glioma local treatment is currently guided by standard MRI sequences. Yet, the combination of apparent diffusion coefficient (ADC) and O-(2-[18F]-fluoroethyl)-L-tyrosine positron emission tomography (FET PET) (ADC/FET) detects histopathological qualitative assessed tumor presence more accurately than standard imaging. It is unknown whether this is similar for quantitative assessed tumor presence. This study compares the diagnostic accuracy of standard imaging and ADC/FET for the detection of quantitative assessed tumor presence in diffuse glioma. MATERIAL AND METHODS Fifteen patients with newly diagnosed diffuse glioma were retrospectively included. Pre-operative standard imaging, ADC and FET PET were available. Multiregional image-guided stereotactic biopsies were acquired before craniotomy. Quantitative imaging data from regions-of-interests (ROIs) centered at the biopsy locations was obtained. For each biopsy, sample semi-automatic cellularity and proliferation index, as well as DNA methylation-based tumor purity was determined. Linear mixed models were used to evaluate which modalities were significant independent predictors for each tumor presence marker and fitness was assessed using Bayesian Information Criterium. RESULTS 125 biopsies were analyzed (75 from eight high grade and 50 from seven low grade gliomas). Cellularity was predicted by T1 weighted MRI (p = 0.033), ADC (p = 0.016) and ADC/FET (p &amp;lt;.001), with ADC/FET as best fit. Both proliferation index (p = 0.003) and tumor purity (p &amp;lt;.001) were only predicted by ADC/FET. CONCLUSION Combining ADC and FET PET predicts cellularity, proliferation index and tumor purity better than standard imaging. Further investigation into ADC/FET-guided local treatment of diffuse glioma is therefore needed.

Initial Experience of 18 F-FET PET-MR Image Fusion for Evaluation of Recurrent Primary Brain Tumors.

Background An accurate monitoring technique is crucial in brain tumors to choose the best treatment approach after surgery and/or chemoradiation. Radiological assessment of brain tumors is widely based on the magnetic resonance imaging (MRI) modality in this regard; however, MRI criteria are unable to precisely differentiate tumoral tissue from treatment-related changes. This study was conducted to evaluate whether fused MRI and O-(2- 18 F-fluoroethyl)-L-tyrosine ( 18 F-FET) positron emission tomography (PET) can improve the diagnostic accuracy of the practitioners to discriminate treatment-related changes from true recurrence of brain tumor. Methods We retrospectively analyzed 18 F-FET PET/computed tomography (CT) of 11 patients with histopathologically proven brain tumors that were suspicious for recurrence changes after 3 to 4 months of surgery. All the patients underwent MRI and 18 F-FET PET/CT. As a third assessment, fused 18 F-FET PET/MRI was also acquired. Finally, the diagnostic accuracy of the applied modalities was compared. Results Eleven patients aged 27 to 73 years with a mean age of 47 ± 13 years were enrolled. According to the results, 9/11 cases (82%) showed positive MRI and 6 cases (55%) showed positive PET/CT and PET/MRI. Tumoral recurrence was observed in six patients (55%) in the follow-up period. Based on the follow-up results, accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 64, 85, 25, 67, and 50%, respectively, for MRI alone and 91, 85, 100, 100, and 80%, respectively, for both PET/CT and PET/MRI. Conclusion This study found that 18 F-FET PET-MR image fusion in the management of brain tumors might improve recurrence detection; however, further well-designed studies are needed to verify these preliminary data.

18F]-fluoroethyl-L-tyrosine (FET) in glioblastoma (FIG) TROG 18.06 study: protocol for a prospective, multicentre PET/CT trial

IntroductionGlioblastoma is the most common aggressive primary central nervous system cancer in adults characterised by uniformly poor survival. Despite maximal safe resection and postoperative radiotherapy with concurrent and adjuvant temozolomide-based...

Radiotherapy Target Volume Definition in Newly Diagnosed High-Grade Glioma Using 18F-FET PET Imaging and Multiparametric MRI: An Inter Observer Agreement Study.

Background: The aim of this prospective monocentric study was to assess the inter-observer agreement for tumor volume delineations by multiparametric MRI and 18-F-FET-PET/CT in newly diagnosed, untreated high-grade glioma (HGG) patients. Methods: Thirty patients HGG underwent O-(2-[18F]-fluoroethyl)-l-tyrosine(18F-FET) positron emission tomography (PET), and multiparametric MRI with computation of rCBV map and K2 map. Three nuclear physicians and three radiologists with different levels of experience delineated the 18-F-FET-PET/CT and 6 MRI sequences, respectively. Spatial similarity (Dice and Jaccard: DSC and JSC) and overlap (Overlap: OV) coefficients were calculated between the readers for each sequence. Results: DSC, JSC, and OV were high for 18F-FET PET/CT, T1-GD, and T2-FLAIR (>0.67). The Spearman correlation coefficient between readers was ≥0.6 for these sequences. Cross-comparison of similarity and overlap parameters showed significant differences for DSC and JSC between 18F-FET PET/CT and T2-FLAIR and for JSC between 18F-FET PET/CT and T1-GD with higher values for 18F-FET PET/CT. No significant difference was found between T1-GD and T2-FLAIR. rCBV, K2, b1000, and ADC showed correlation coefficients between readers <0.6. Conclusion: The interobserver agreements for tumor volume delineations were high for 18-F-FET-PET/CT, T1-GD, and T2-FLAIR. The DWI (b1000, ADC), rCBV, and K2-based sequences, as performed, did not seem sufficiently reproducible to be used in daily practice.

Diagnostic yield of simultaneous dynamic contrast-enhanced magnetic resonance perfusion measurements and [18F]FET PET in patients with suspected recurrent anaplastic astrocytoma and glioblastoma

PurposeBoth amino acid positron emission tomography (PET) and magnetic resonance imaging (MRI) blood volume (BV) measurements are used in suspected recurrent high-grade gliomas. We compared the separate and combined diagnostic yield of simultaneously acquired dynamic contrast-enhanced (DCE) perfusion MRI and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET in patients with anaplastic astrocytoma and glioblastoma following standard therapy.MethodsA total of 76 lesions in 60 hybrid [18F]FET PET/MRI scans with DCE MRI from patients with suspected recurrence of anaplastic astrocytoma and glioblastoma were included retrospectively. BV was measured from DCE MRI employing a 2-compartment exchange model (2CXM). Diagnostic performances of maximal tumour-to-background [18F]FET uptake (TBRmax), maximal BV (BVmax) and normalised BVmax (nBVmax) were determined by ROC analysis using 6-month histopathological (n = 28) or clinical/radiographical follow-up (n = 48) as reference. Sensitivity and specificity at optimal cut-offs were determined separately for enhancing and non-enhancing lesions.ResultsIn progressive lesions, all BV and [18F]FET metrics were higher than in non-progressive lesions. ROC analyses showed higher overall ROC AUCs for TBRmax than both BVmax and nBVmax in both lesion-wise (all lesions, p = 0.04) and in patient-wise analysis (p < 0.01). Combining TBRmax with BV metrics did not increase ROC AUC. Lesion-wise positive fraction/sensitivity/specificity at optimal cut-offs were 55%/91%/84% for TBRmax, 45%/77%/84% for BVmax and 59%/84%/72% for nBVmax. Combining TBRmax and best-performing BV cut-offs yielded lesion-wise sensitivity/specificity of 75/97%. The fraction of progressive lesions was 11% in concordant negative lesions, 33% in lesions only BV positive, 64% in lesions only [18F]FET positive and 97% in concordant positive lesions.ConclusionThe overall diagnostic accuracy of DCE BV imaging is good, but lower than that of [18F]FET PET. Adding DCE BV imaging did not improve the overall diagnostic accuracy of [18F]FET PET, but may improve specificity and allow better lesion-wise risk stratification than [18F]FET PET alone.

Glioma Imaging by O-(2-18F-Fluoroethyl)-L-Tyrosine PET and Diffusion-Weighted MRI and Correlation With Molecular Phenotypes, Validated by PET/MR-Guided Biopsies.

Gliomas exhibit high intra-tumoral histological and molecular heterogeneity. Introducing stereotactic biopsy, we achieved a superior molecular analysis of glioma using O-(2-18F-fluoroethyl)-L-tyrosine (FET)-positron emission tomography (PET) and diffusion-weighted magnetic resonance imaging (DWI). Patients underwent simultaneous DWI and FET-PET scans. Correlations between biopsy-derived tumor tissue values, such as the tumor-to-background ratio (TBR) and apparent diffusion coefficient (ADC)/exponential ADC (eADC) and histopathological diagnoses and those between relevant genes and TBR and ADC values were determined. Tumor regions with human telomerase reverse transcriptase (hTERT) mutation had higher TBR and lower ADC values. Tumor protein P53 mutation correlated with lower TBR and higher ADC values. α-thalassemia/mental-retardation-syndrome-X-linked gene (ATRX) correlated with higher ADC values. 1p/19q codeletion and epidermal growth factor receptor (EGFR) mutations correlated with lower ADC values. Isocitrate dehydrogenase 1 (IDH1) mutations correlated with higher TBRmean values. No correlation existed between TBRmax/TBRmean/ADC/eADC values and phosphatase and tensin homolog mutations (PTEN) or O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation. Furthermore, TBR/ADC combination had a higher diagnostic accuracy than each single imaging method for high-grade and IDH1-, hTERT-, and EGFR-mutated gliomas. This is the first study establishing the accurate diagnostic criteria for glioma based on FET-PET and DWI.

PET/MR in recurrent glioblastoma patients treated with regorafenib: [18F]FET and DWI-ADC for response assessment and survival prediction.

Objective:The use of regorafenib in recurrent glioblastoma patients has been recently approved by the Italian Medicines Agency (AIFA) and added to the National Comprehensive Cancer Network (NCCN) 2020 guidelines as a preferred regimen. Given its complex effects at the molecular level, the most appropriate imaging tools to assess early response to treatment is still a matter of debate. Diffusion-weighted imaging and O-(2-18F-fluoroethyl)-L-tyrosine positron emission tomography ([18F]FET PET) are promising methodologies providing additional information to the currently used RANO criteria. The aim of this study was to evaluate the variations in diffusion-weighted imaging/apparent diffusion coefficient (ADC) and [18F]FET PET-derived parameters in patients who underwent PET/MR at both baseline and after starting regorafenib.Methods:We retrospectively reviewed 16 consecutive GBM patients who underwent [18F]FET PET/MR before and after two cycles of regorafenib. Patients were sorted into stable (SD) or progressive disease (PD) categories in accordance with RANO criteria. We were also able to analyze four SD patients who underwent a third PET/MR after another four cycles of regorafenib. [18F]FET uptake greater than 1.6 times the mean background activity was used to define an area to be superimposed on an ADC map at baseline and after treatment. Several metrics were then derived and compared. Log-rank test was applied for overall survival analysis.Results:Percentage difference in FET volumes correlates with the corresponding percentage difference in ADC (R = 0.54). Patients with a twofold increase in FET after regorafenib showed a significantly higher increase in ADC pathological volume than the remaining subjects (p = 0.0023). Kaplan–Meier analysis, performed to compare the performance in overall survival prediction, revealed that the percentage variations of FET- and ADC-derived metrics performed at least as well as RANO criteria (p = 0.02, p = 0.024 and p = 0.04 respectively) and in some cases even better. TBR Max and TBR mean are not able to accurately predict overall survival.ConclusionIn recurrent glioblastoma patients treated with regorafenib, [18F]FET and ADC metrics, are able to predict overall survival and being obtained from completely different measures as compared to RANO, could serve as semi-quantitative independent biomarkers of response to treatment.Advances in knowledgeSimultaneous evaluation of [18F]FET and ADC metrics using PET/MR allows an early and reliable identification of response to treatment and predict overall survival.

Negative 18F-FET PET/CT in brain metastasis recurrence: a teaching case report

Positron emission tomography (PET) using O-(2-[18F]fluoroethyl)-L-tyrosine (18F-FET) PET has been shown to be a useful tool for differentiating radiation therapy outcomes, such as brain metastasis recurrence or radiation necrosis. We present the case of a female patient with brain metastases from pulmonary mucinous adenocarcinoma with suspicion of tumor recurrence on follow-up magnetic resonance imaging (MRI) after radiosurgery. 18F-FET PET/computed tomography (CT) was indicative of radiation necrosis. Due to the patient's medical history and the discrepancy between the brain MRI and PET/CT results, surgical biopsies were decided, which were positive for brain metastasis recurrence. The diagnosis of metastasis recurrence may also be challenging on 18F-FET PET/CT. In case of discrepancies between MRI and PET/CT results, false-negative 18F-FET PET/CT remains a possibility and requires careful follow-up or biopsy.

Visualizing cellularity and angiogenesis in newly-diagnosed glioblastoma with diffusion and perfusion MRI and FET-PET imaging

PurposeCombining imaging modalities has become an essential tool for assessment of tumor biology in glioblastoma (GBM) patients. Aim of this study is to understand how tumor cellularity and neovascularization are reflected in O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography ([18F] FET PET) and magnetic resonance imaging (MRI) parameters, including cerebral blood volume (CBV), fractional anisotropy (FA) and mean diffusivity (MD).MethodsIn this prospective cohort, 162 targeted biopsies of 43 patients with therapy-naïve, isocitrate dehydrogenase (IDH) wildtype GBM were obtained after defining areas of interest based on imaging parameters [18F] FET PET, CBV, FA and MD. Histopathological analysis of cellularity and neovascularization was conducted and results correlated to imaging data.ResultsANOVA analysis showed a significant increase of CBV in areas with high neovascularization. For diffusion metrics, and in particular FA, a trend for inverse association with neovascularization was found. [18F] FET PET showed a significant positive correlation to cellularity, while CBV also showed a trend towards correlation with cellularity, not reaching significant levels. In contrast, MD and FA were negatively associated with cellularity.ConclusionOur study confirms that amino acid PET and MR imaging parameters are indicative of histological tumor properties in glioblastoma and highlights the ability of multimodal imaging to assess tumor biology non-invasively.

Machine learning-based differentiation between multiple sclerosis and glioma WHO II°-IV° using O-(2-[18F] fluoroethyl)-L-tyrosine positron emission tomography.

This study aimed to test the diagnostic significance of FET-PET imaging combined with machine learning for the differentiation between multiple sclerosis (MS) and glioma II°-IV°. Our database was screened for patients in whom FET-PET imaging was performed for the diagnostic workup of newly diagnosed lesions evident on MRI and suggestive of glioma. Among those, we identified patients with histologically confirmed glioma II°-IV°, and those who later turned out to have MS. For each group, tumor-to-brain ratio (TBR) derived features of FET were determined. A support vector machine (SVM) based machine learning algorithm was constructed to enhance classification ability, and Receiver Operating Characteristic (ROC) analysis with area under the curve (AUC) metric served to ascertain model performance. A total of 41 patients met selection criteria, including seven patients with MS and 34 patients with glioma. TBR values were significantly higher in the glioma group (TBRmax glioma vs. MS: p = 0.002; TBRmean glioma vs. MS: p = 0.014). In a subgroup analysis, TBR values significantly differentiated between MS and glioblastoma (TBRmax glioblastoma vs. MS: p = 0.0003, TBRmean glioblastoma vs. MS: p = 0.0003) and between MS and oligodendroglioma (ODG) (TBRmax ODG vs. MS: p = 0.003; TBRmean ODG vs. MS: p = 0.01). The ability to differentiate between MS and glioma II°-IV° increased from 0.79 using standard TBR analysis to 0.94 using a SVM based machine learning algorithm. FET-PET imaging may help differentiate MS from glioma II°-IV° and SVM based machine learning approaches can enhance classification performance.

18F]FET PET Uptake Indicates High Tumor and Low Necrosis Content in Brain Metastasis.

Simple SummaryVarious types of cancers can lead to brain metastasis. Treatment strategies have improved substantially in the past decade, leading to longer survival in many cases, but also to new diagnostic challenges. Being able to locate those parts of a lesion suspicious for brain metastasis that contain the highest concentrations of viable tumor cells can be crucial, e.g., to obtain a precise diagnosis via targeted biopsies or to differentiate recurring tumor from dead tissue after treatment. Positron emission tomography (PET) imaging has the potential to provide this kind of information. However, studies relating PET findings to actual tissue properties are sparse. The aim of this study was to investigate the association of PET imaging with microscopic tissue properties in samples obtained neurosurgically from brain metastases. Our findings can improve the planning and yield of biopsies from brain metastases, and they may inform future studies aimed at improving the discrimination of recurring from dead tumor in treated brain metastases using PET.Amino acid positron emission tomography (PET) has been employed in the management of brain metastases. Yet, histopathological correlates of PET findings remain poorly understood. We investigated the relationship of O-(2-[18F]Fluoroethyl)-L-tyrosine ([18F]FET) PET, magnetic resonance imaging (MRI), and histology in brain metastases. Fifteen patients undergoing brain metastasis resection were included prospectively. Using intraoperative navigation, 39 targeted biopsies were obtained from parts of the metastases that were either PET-positive or negative and MRI-positive or negative. Tumor and necrosis content, proliferation index, lymphocyte infiltration, and vascularization were determined histopathologically. [18F]FET PET had higher specificity than MRI (66% vs. 56%) and increased sensitivity for tumor from 73% to 93% when combined with MRI. Tumor content per sample increased with PET uptake (rs = 0.3, p = 0.045), whereas necrosis content decreased (rs = −0.4, p = 0.014). PET-positive samples had more tumor (median: 75%; interquartile range: 10–97%; p = 0.016) than PET-negative samples. The other investigated histological properties were not correlated with [18F]FET PET intensity. Tumors were heterogeneous at the levels of imaging and histology. [18F]FET PET can be a valuable tool in the management of brain metastases. In biopsies, one should aim for PET hotspots to increase the chance for retrieval of samples with high tumor cell concentrations. Multiple biopsies should be performed to account for intra-tumor heterogeneity. PET could be useful for differentiating treatment-related changes (e.g., radiation necrosis) from tumor recurrence.

Heterogeneous parameters based on 18F-FET PET imaging can non-invasively predict tumor grade and isocitrate dehydrogenase gene 1 mutation in untreated gliomas.

The present study aimed to explore the efficacy of easily obtained intratumoral heterogeneous parameters, other than regular semi-quantitative parameters, based on static O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) positron emission tomography (PET) imaging in glioma grade and isocitrate dehydrogenase (IDH) gene 1 mutation prediction. Fifty-eight adult patients with untreated glioma (grades II-IV) who underwent preoperative 18F-FET PET/computed tomography (CT) imaging were enrolled in the present study. Eight semi-automatically obtained static PET imaging parameters after lesion delineation were chosen for analysis. These were: maximal tumor-to-background ratio (TBRmax), peak tumor-to-background ratio (TBRpeak), mean tumor-to-background ratio (TBRmean), coefficient of variation (COV), heterogeneity index (HI), the standard deviation of lesion standardized uptake value (SUVsd), metabolic tumor volume (MTV), and total lesion tracer standardized uptake (TLU). Pathological and immunohistochemical results were used as a reference. The receiver-operating characteristic analysis was used to investigate the predictive efficacy of these parameters in glioma grade and IDH1 mutation status. TLU [area under the curve (AUC): 0.841, P<0.0001], TBRpeak (AUC: 0.832, P<0.0001), and HI (AUC: 0.826, P<0.0001) had the top 3 single-parameter predictive performance between grade II or III and grade IV glioma patients. Combinations of TBRmax, SUVsd, and TBRmean (AUC: 0.850, P<0.0001); HI, SUVsd, and MTV (AUC: 0.848, P<0.0001); and HI, SUVsd, and TLU (AUC: 0.848, P<0.0001) had the top 3 multiple-parameter predictive performance. SUVsd (AUC: 0.710, P=0.0028), TLU (AUC: 0.698, P=0.0074), and HI (AUC: 0.676, P=0.0159) had the top 3 single-parameter predictive performance in the IDH1 genotype. Combinations of TBRmax, SUVsd, and TBRmean (AUC: 0.821, P<0.0001); SUVsd and TBRmean (AUC: 0.804, P<0.0001); and SUVsd, HI, and TBRmean (AUC: 0.799, P<0.0001) had the top 3 multiple-parameter predictive performance. These easily obtained and highly repetitive heterogeneous parameters based on static 18F-FET PET/CT imaging can non-invasively predict glioma grade and IDH1 mutation, crucial in treatment planning, and prognostic evaluation.

FET PET Radiomics for Differentiating Pseudoprogression from Early Tumor Progression in Glioma Patients Post-Chemoradiation.

Simple SummaryFollowing chemoradiation with alkylating agents in glioma patients, structural magnetic resonance imaging (MRI) may suggest tumor progression which subsequently improves during the course of the disease without any treatment change. This phenomenon has been termed pseudoprogression. Despite advances in medical imaging, a reliable diagnosis of pseudoprogression remains a challenging task. Radiomics is a subdiscipline of artificial intelligence and allows the identification and extraction of imaging features from various routine imaging modalities. These features can be used for the generation of mathematical models to improve diagnostics in patients with brain tumors. The present study highlights the potential of radiomics obtained from amino acid positron emission tomography (PET) for the diagnosis of pseudoprogression. In 34 patients with suspicious MRI early after chemoradiation completion, our radiomics model correctly identified all patients with pseudoprogression.Currently, a reliable diagnostic test for differentiating pseudoprogression from early tumor progression is lacking. We explored the potential of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) radiomics for this clinically important task. Thirty-four patients (isocitrate dehydrogenase (IDH)-wildtype glioblastoma, 94%) with progressive magnetic resonance imaging (MRI) changes according to the Response Assessment in Neuro-Oncology (RANO) criteria within the first 12 weeks after completing temozolomide chemoradiation underwent a dynamic FET PET scan. Static and dynamic FET PET parameters were calculated. For radiomics analysis, the number of datasets was increased to 102 using data augmentation. After randomly assigning patients to a training and test dataset, 944 features were calculated on unfiltered and filtered images. The number of features for model generation was limited to four to avoid data overfitting. Eighteen patients were diagnosed with early tumor progression, and 16 patients had pseudoprogression. The FET PET radiomics model correctly diagnosed pseudoprogression in all test cohort patients (sensitivity, 100%; negative predictive value, 100%). In contrast, the diagnostic performance of the best FET PET parameter (TBRmax) was lower (sensitivity, 81%; negative predictive value, 80%). The results suggest that FET PET radiomics helps diagnose patients with pseudoprogression with a high diagnostic performance. Given the clinical significance, further studies are warranted.

Static 18F-FET PET and DSC-PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status.

To investigate the predictive value of static O-(2-18F-fluoroethyl)-L-tyrosine positron emission tomography (18F-FET PET) and cerebral blood volume (CBV) for glioma grading and determining isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status. Fifty-two patients with newly diagnosed gliomas who underwent simultaneous 18F-FET PET and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) examinations on hybrid PET/MR were retrospectively enrolled. The mean and max tumor-to-brain ratio (TBR) and normalized CBV (nCBV) were calculated based on whole tumor volume segmentations with reference to PET/MR images. The predictive efficacy of FET PET and CBV in glioma according to the 2016 World Health Organization (WHO) classification was evaluated by receiver operating characteristic curve analyses with the area under the curve (AUC). TBRmean, TBRmax, nCBVmean, and nCBVmax differed between low- and high-grade gliomas, with the highest AUC of nCBVmean (0.920). TBRmax and nCBVmean showed significant differences between gliomas with and without IDH mutation (p = 0.032 and 0.010, respectively). Furthermore, TBRmean, TBRmax, and nCBVmean discriminated between IDH-wildtype glioblastomas and IDH-mutated astrocytomas (p = 0.049, 0.034 and 0.029, respectively). The combination of TBRmax and nCBVmean showed the best predictive performance (AUC, 0.903). Only nCBVmean differentiated IDH-mutated with 1p/19q codeletion oligodendrogliomas from IDH-wildtype glioblastomas (p < 0.001) (AUC, 0.829), but none of the parameters discriminated between oligodendrogliomas and astrocytomas. Both FET PET and DSC-PWI might be non-invasive predictors for glioma grades and IDH mutation status. FET PET combined with CBV could improve the differentiation of IDH-mutated astrocytomas and IDH-wildtype glioblastomas. However, FET PET and CBV might be limited for identifying oligodendrogliomas. • Static 18F-FET PET and DSC-PWI parameters differed between low- and high-grade gliomas, with the highest AUC of the mean value of normalized CBV. • Static 18F-FET PET and DSC-PWI parameters based on hybrid PET/MR showed predictive value in identifying glioma IDH mutation subtypes, which have gained importance for both determining the diagnosis and prognosis of gliomas according to the 2016 WHO classification. • Static 18F-FET PET and DSC-PWI parameters have limited potential in differentiating IDH-mutated with 1p/19q codeletion oligodendrogliomas from IDH-wildtype glioblastomas or IDH-mutated astrocytomas.